Data availability statements are now a standard requirement in many academic journals, especially in STEM, social sciences, medicine, psychology, and AI-related fields. These statements tell editors, reviewers, and readers where your study’s data can be accessed, under what conditions, and how they can be reused. They are key to transparency, reproducibility, and open science. Yet many researchers—especially students and early-career authors—struggle with writing them correctly. This guide explains how to prepare a data availability statement for academic journals, with examples you can adapt immediately.
What Is a Data Availability Statement (DAS)?
A Data Availability Statement (DAS) is a short declaration in your manuscript explaining:
- Whether your data is available
- Where it is stored
- How others can access it
- Any restrictions (ethical, legal, or proprietary)
- Why data may not be publicly available
It is typically placed at the end of the manuscript or in a designated “Data Availability” section during submission.
Why Journals Require a Data Availability Statement
Data availability is a core part of modern academic publishing because it:
1. Improves transparency
Readers understand how results were produced.
2. Enables reproducibility
Others can verify, replicate, or extend your study.
3. Supports open science
Many funders (NIH, NSF, UKRI, Horizon Europe) now require open data when possible.
4. Increases visibility and citation rates
Studies with open data tend to be cited more often.
5. Ensures ethical compliance
Readers can see when data is restricted—for privacy or safety reasons.
A clear DAS strengthens the credibility of your research.
Types of Data Availability Statements
Different journals accept different forms of DAS depending on the nature of your data. Here are the six most common categories.
1. Openly Available Data
Data is uploaded to a public repository and can be accessed without restriction.
Best for:
- Non-sensitive datasets
- Simulated data
- Basic research
- Environmental data
- Experimental results
2. Restricted Data (Available Upon Request)
Data cannot be shared publicly but may be available with conditions, such as:
- Ethical approval
- Institutional restrictions
- Privacy protections
3. No Data Created or Analyzed
Used for:
- Conceptual papers
- Literature reviews
- Theoretical essays
4. Proprietary or Commercially Sensitive Data
Data cannot be shared due to:
- NDAs
- Industry partnerships
- Commercial licensing
5. Human Participant Data (Ethically Restricted)
Most journals require anonymization before sharing, but some data cannot be shared at all.
Used when:
- Participants might be identifiable
- Cultural or legal restrictions apply
- Sensitive populations are involved
6. Data in Supplementary Materials
Data included:
- In the manuscript appendix
- In supplementary files
- In tables or figures
How to Prepare a Data Availability Statement (Step-by-Step)
Follow below mentioned steps to write better DAS:
Step 1: Determine Whether Your Data Can Be Shared
Ask:
- Does the data contain personal identifiers?
- Does your ethics approval allow sharing?
- Does the data belong to you, your institution, or a third party?
- Does your funder require open data?
If unsure → consult your supervisor or ethics board.
Step 2: Choose the Right Repository
Journals increasingly prefer FAIR-compliant repositories:
General-purpose:
- Zenodo
- Figshare
- Dryad
- OSF (Open Science Framework)
Domain-specific:
- ICPSR (social science)
- GenBank (biology)
- UK Data Service
- Kaggle (machine learning)
Institutional repositories:
- University-run archives
- Private research institution databases
Step 3: Upload Your Data and Metadata
Metadata should include:
- Variable definitions
- Data dictionary
- Sampling process
- Instructions for reuse
- Codebooks
- README files
- Analysis scripts (R, Python, SPSS, etc.)
Tools like ResearchPal’s Reference Manager and Paper Insights help document methods clearly.
Step 4: Generate a Permanent Link or DOI
Repositories like Zenodo and Figshare automatically generate a DOI for datasets.
This DOI is included in your data availability statement.
Step 5: Write the Data Availability Statement Using Clear Templates
Below are ready-to-use examples.
Examples of Data Availability Statements
1. Data Openly Available (No Restrictions)
“The dataset generated for this study is available in the Zenodo repository at: https://doi.org/xxxxx. All data files and analysis scripts are included.”
2. Data Available Upon Reasonable Request
“Due to ethical restrictions related to participant confidentiality, the dataset supporting this study is available from the corresponding author upon reasonable request and pending institutional approval.”
3. Data Not Shared Due to Privacy Restrictions
“Human participant data cannot be shared publicly due to ethical and privacy restrictions. The data contains potentially identifying information. Data access requests may be submitted to the ethics board at [Institution].”
4. Data Provided by a Third Party
“The data used in this study were obtained from [Organization] and are subject to licensing restrictions. Researchers may request access from [Contact Information].”
5. No Data Collected or Analyzed
“This study does not include primary data. All analysis is based on previously published literature.”
6. Data Included in Supplementary Files
“All data generated or analyzed during this study are included in this published article and its supplementary information files.”
7. Code Shared Separately
“Analysis scripts used in this study are available on GitHub at: https://github.com/xxxx. The associated dataset can be found at https://doi.org/xxxx.”
Common Mistakes to Avoid
Avoid:
❌ Vague statements like “Data available upon request” with no explanation
❌ Saying data is open when it isn’t
❌ Sharing identifiable participant data
❌ Linking to unstable storage (e.g., Google Drive)
❌ Not including metadata or documentation
❌ Omitting code or scripts when journals require them
❌ Violating ethical or legal restrictions
Transparency + compliance = a strong DAS.
How ResearchPal Helps You Prepare a Strong Data Availability Statement
ResearchPal streamlines your DAS preparation through:
✔ Paper Insights
See how similar studies phrased their statements.
~Learn more
✔ Chat With PDF
Ask methodological papers:
- “Does this study include a data availability statement?”
- “How did they justify data restrictions?”
✔ AI-Powered Writing & Paraphrasing Tools
Draft and refine professional DAS statements.
~Learn more
✔ Literature Review Tools
Find domain repositories used in your field.
~Learn more
✔ Citation Generator & Reference Manager
Create accurate citations for datasets and code repositories.
ResearchPal supports ethical, transparent, reproducible research workflows.
~Learn more
Related Reading
From the Web
- Springer Nature — Guide to Data Availability Statements:
https://www.springernature.com/gp/authors/research-data-policy/data-availability-statements - PLOS — Data Policy and Sharing Guidelines:
https://journals.plos.org/plosone/s/data-availability
Final Thoughts
Learning how to prepare a data availability statement for academic journals is essential for modern research. A clear, transparent DAS not only meets journal requirements but also enhances credibility, reproducibility, and academic impact. By choosing the right repository, documenting your data properly, and using accurate templates, you can create a professional statement that supports open, ethical scientific practice.
